Leukemia, one of the top 10 most frequently occurring cancers in all races and ethnicities, is characterized by the aberrant activity of oncogenic transcription factors that lead to impaired hematopoietic differentiation. Systematic characterization of the transcriptional regulatory network controlling the hematopoietic lineage will enable us to understand the role of pathogenic changes, improve diagnosis, and discover new therapeutic targets. Very recent studies in human hematopoiesis from our laboratory show that hundreds of transcription factors participate in orchestrating hematopoiesis, including 30 that were found in translocations in leukemia. However, due to the limitations of current assays (e.g. chromatin immunoprecipitation assay, ChIP), deciphering the direct connections between these transcription factors and their targets remains an elusive goal. Here, I will build a comprehensive physical regulatory network of 100 lineage specific and malignancy-related transcription factors in the four main terminally differentiated human hematopoietic cell populations, by employing a novel, high throughput ChIP-seq assay developed by our laboratory. I will use computational algorithms to construct a predictive functional regulatory model that integrates the physical binding network with the gene expression profiles it controls. Together with gene expression profiles measured from patient's samples, the model will be used to predict malignant transcriptional regulatory circuits. Finally, I will validate and refine he model using expression profiles from knockdowns of selected key transcription factors. This study will substantially enhance our understanding of hematopoietic differentiation and leukemia pathogenesis, towards personalized diagnoses and therapeutics.